Effective Roughness Calculated from Satellite-Derived Land Cover Maps and Hedge-Information used in a Weather Forecasting Model

In numerical weather prediction, climate and hydrologicalmodelling, the grid cell size is typically larger than the horizontal length scales of variations in aerodynamicroughness, surface temperature and surface humidity. These local land cover variations give rise to sub-gridscale surface flux differences. Especially the roughness variations can give a significantly differentvalue between the equilibrium roughness in each of the patches as compared to the aggregated roughness value,the so-called effective roughness, for the grid cell. The effective roughness is a quantity that secures thephysics to be well-described in any large-scale model. A method of aggregating the roughness step changesin arbitrary real terrain has been applied in flat terrain (Denmark) where sub-grid scale vegetation-drivenroughness variations are a dominant characteristic of the landscape. The aggregation model is a physicaltwo-dimensional atmospheric flow model in the horizontal domain based on a linearized version of theNavier Stoke equation. The equations are solved by the Fast Fourier Transformation technique, hence the codeis very fast. The new effective roughness maps have been used in the HIgh Resolution Limited Area Model(HIRLAM) weather forecasting model and the weather prediction results are compared for a number of casesto synoptic and other observations with improved agreement above the predictions based on currentstandard input. Typical seasonal springtime bias on forecasted winds over land of +0.5 m s-1 and-0.2 m s-1 in coastal areas is reduced by use of the effective roughness maps.

[1]  P. J. Mason,et al.  The formation of areally‐averaged roughness lengths , 1988 .

[2]  Robert E. Dickinson,et al.  Simulating fluxes from heterogeneous land surfaces: Explicit subgrid method employing the biosphere‐atmosphere transfer scheme (BATS) , 1994 .

[3]  S. Belcher,et al.  On the Parameterisation of the Effective Roughness Length for Momentum Transfer over Heterogeneous Terrain , 1999 .

[4]  Ann Henderson-Sellers,et al.  Biosphere-atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model , 1986 .

[5]  Hans Peter Schmid,et al.  The influence of surface texture on the effective roughness length , 1995 .

[6]  A. Thom.  Momentum absorption by vegetation , 1971 .

[7]  H. Lettau.  Note on Aerodynamic Roughness-Parameter Estimation on the Basis of Roughness-Element Description , 1969 .

[8]  W. Bastiaanssen,et al.  A remote sensing surface energy balance algorithm for land (SEBAL). , 1998 .

[9]  Michael R. Raupach,et al.  Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index , 1994 .

[10]  Massimo Menenti,et al.  Aggregation effects of surface heterogeneity in land surface processes , 1999 .

[11]  J. Redelsperger,et al.  A turbulence scheme allowing for mesoscale and large‐eddy simulations , 2000 .

[12]  A. Holtslag,et al.  A remote sensing surface energy balance algorithm for land (SEBAL)-1. Formulation , 1998 .

[13]  Jon Wiernga.  Representative roughness parameters for homogeneous terrain , 1993 .

[14]  N. Jensen,et al.  Internal equilibrium layer growth over forest , 2000 .

[15]  M. Claussen,et al.  LANDSCAPE VARIABILITY AND SURFACE FLUX PARAMETERIZATION IN CLIMATE MODELS , 1995 .

[16]  E. Boegh,et al.  Estimating transpiration rates in a Danish agricultural area using landsat thermal mapper data , 2000 .

[17]  Martin Claussen,et al.  Estimation of areally-averaged surface fluxes , 1991 .

[18]  J. Gash,et al.  A note on estimating the effect of a limited fetch on micrometeorological evaporation measurements , 1986 .

[19]  J. Walmsley,et al.  A simple model of neutrally stratified boundary-layer flow over complex terrain with surface roughness modulations (MS3DJH/3R) , 1986 .

[20]  IRS-1C LISS III land cover maps at different spatial resolutions used in real-time accidental air pollution deposition modelling , 2001 .

[21]  M. Claussen.  Estimation of regional heat and moisture fluxes in homogeneous terrain with bluff roughness elements , 1995 .

[22]  Charlotte Bay Hasager,et al.  Carbon dioxide exchange over agricultural landscape using eddy correlation and footprint modelling , 2003 .

[23]  S. Hagemann,et al.  High resolution physiographic data set for HIRHAM4: An application to a 50 km horizontal resolution domain covering Europe , 2001 .

[24]  Charlotte Bay Hasager,et al.  Surface‐flux aggregation in heterogeneous terrain , 1999 .

[25]  C. Hasager,et al.  Regional Fluxes Of Momentum And Sensible Heat Over A Sub-Arctic Landscape During Late Winter , 2001 .

[26]  L.J.M. Kroon,et al.  Fluxes in the Surface Layer Under Advective Conditions , 1991 .

[27]  Roni Avissar,et al.  A statistical-dynamical approach to parameterize subgrid-scale land-surface heterogeneity in climate models , 1991 .

[28]  Measurements of ammonia flux to a spruce stand in Denmark , 1993 .

[29]  M. Claussen,et al.  The atmospheric general circulation model ECHAM-4: Model description and simulation of present-day climate , 1996 .

[30]  A. Beljaars,et al.  Surface layer Similarity under Nonuniform Fetch Conditions. , 1983 .

[31]  Niels Gylling Mortensen,et al.  Response of neutral boundary layers to changes of roughness , 1990 .